Apologies if this question is trivially easy, I'm still learning Tableau.
I have data where the variables Set and Subset are arranged by week (W1 to W52) and by Source (A or B). So if I put Week into Rows and create the calculated fields
SUM(Set)
SUM(Subset)
Rate = {INCLUDE Source: SUM(Subset) / SUM(Set)}
I get data that look like this:
Week SUM(Set) SUM(Subset) Rate
A B A B A B
W1 1234 123 567 56 45.95% 45.53%
So far, so good. But what I really want is the percentage difference between Rate(A) and Rate(B) by week:
Diff = (Rate.A - Rate.B) / Rate.B
I could do this in a second if I were using Excel or R, but I can't seem to figure out how Tableau does it. Help?
There's a built in table calculation "Percent Difference" , you can deploy it using compute using Table across and relative to previous. For that you need to have continuous measures.
Something like this will be the calculation-:
(ZN(SUM([Quantity])) - LOOKUP(ZN(SUM([Quantity])), -1)) / ABS(LOOKUP(ZN(SUM([Quantity])), -1))
Create two different for "Set" & "Subset"
Related
I want to compare how different campaigns are progressing based on number of days into the campaign rather than by date (see day1, day2, etc... on the x-axis below).
Here is my DAX code, but I can't get it to work. Any help would be much appreciated...
**Normalised Campaign Metrics =
VAR DateReached = CALCULATE(MIN(Days[Day]),db[PAYMENT_DATE]<> BLANK(), KEEPFILTERS(db[PRODUCT_CODE SWITCH]))
VAR MaxDate = CALCULATE(MAX(db[PAYMENT_DATE]),KEEPFILTERS(db[PRODUCT_CODE SWITCH]))
VAR DayNo = SELECTEDVALUE(Days[Day])
RETURN CALCULATE(count(db[PAYMENT_DATE]),
FILTER(ALL(db[PAYMENT_DATE]),
DateReached+DayNo && DateReached+DayNo<=MaxDate))**
Many thanks!
enter image description here
I would recommend solving this through manipulating your actual data rather than a complex DAX measure. If you are familiar with star schema modelling, I would solve this problem by adding a new column to your fact table that calculates how many days from the start date the payment occurred and then connect this column to a new "Days Passed" dimension that is simply a list of numbers from 1 to however many days you need. Then, you can use this new dimension as the source data for your x axis and use a standard payment amount measure for your y axis.
I recommend to create a dimension table as the relative basis to comparison with inactive relationship. Here is a video about it:
https://youtu.be/knXFVf2ipro
looking to have a basic text grid by month by product, and then have a single filter on only 2 of the measures. For example:
Measures Filter
------------------
[ ] Sales <-- only show this
[X] Quantity <-- and this as options
[ ] Interest (don't show in filter)
[ ] Fee ( don't show in filter)
JAN | FEB | MAR | APR | MAY | etc ...
products
ITEM1 x x x x x
ITEM2 x x x x x
ITEM3 x x x x x
So the user can basically toggle between Sales or Quantity, and whichever they click on will fill out the x by month.
I was able to get this to work for everything except only showing the 2 measures I want to filter for. It only shows all measures for me in the filter and I can't figure out how to hide them.
What I did was
Drag Date to columns
Drag Product and MeasureNames to Rows
Can someone please help me on getting this correct? Any help or guidance is appreciated!
This is not the correct use case of FILTERS. Filters are normally used to filter (read subset) the data (read rows). Say for example If your dataset has 1000 rows/records and you want some report/visual/aggregation on say 500 rows (based on some criteria of course) you have to filter the data. For selection of argument (user based) in some report/viz, etc. Parameters are used.
Your desired example output is also a perfect case of use of Parameters. You may proceed as follows-
Step-1 Create a parameter (say parameter 1) with values as SALES and QUANTITY.
Step-2 Create a calculated field (say CF1) with the following calculation
CASE [parameter 1]
WHEN 'SALES` THEN [sales]
WHEN 'Quantity' then [Quantity]
END
Note: It is assumed that your field/column names in dataset are sales and Quantity
Step-3 Build your view (Crosstab here) with
months on Columns shelf
products on rows shelf
CF1 on text in Marks card (alternatively just double click it)
Choose measure for aggregation of CF1 as desired (default will be sum)
Step-4 right click paramter 1 and click show parameter. (select desired measure for aggregation in crosstab)
VOILA your desired view is complete. Good luck.
There is another options to add to Anil's good suggestion. You can also use Measure Names as a filter. Hide all measures apart from those you want in the filter, then put Measure Names on the filter shelf.
However, this means you can't use the hidden measures from the data source elsewhere, which can be a deal breaker. Duplicating the data source is a way around that limitation.
But if you only want to show the 2 measures and are happy with single select, then choosing the measure by parameter is the better option, as Anil suggests.
i'm totally new to Tableau but that is what I could potentially use at the workplace, so asking this question to decide if its worth it.
I've a monthly values dataset and I'd like the tool (Tableau) to generate a report to point out anomalies - the ones i have in mind right now are:
1) same data value for x months in a row
2) data value is 0
3) 5 parameters been reported last 3 months and all of sudden only 4 are reported
Is this possible in Tableau?
You can certainly do this. The below is a general example for doing anomaly detection (one standard deviation outside of mean) but you can modify the calc to fit your criteria. If you place your date field in the column position and your metric, lets say Sales, in the row position you can then create this calculated field to label the anomalies.
IF SUM([Sales]) < (WINDOW_AVG(SUM([Sales])) – WINDOW_STDEV(SUM([Sales]))) THEN “Bad
Anomaly”
ELSEIF SUM([Sales]) > (WINDOW_AVG(SUM([Sales])) + WINDOW_STDEV(SUM([Sales]))) THEN
“Good Anomaly”
ELSE “Expected”
END
You can then place the new field on your color mark to highlight each of the results.
I have a data set downloaded from the Social Security website. The data is in the form below, and contains the popularity (i.e., as defined by Count) of names, by gender, year and state:
State Gender Year Name Count First Letter
AK F 1910 Anna 10 A
AK F 1910 Annie 12 A
AK F 1911 Annie 6 A
AK F 1912 Alice 5 A
AK M 1912 Wilbur 7 W
AK M 1912 Thomas 7 T
Within Tableau, I'd like to Top X names by each of these categories (or all if not filters are applied). However, when I use a Top filter in a visualization, the underlying data produced by the filter is the form:
For example, I need the first ranked name, and be able to use filters to see how that changes by year, gender, and state. I'm thinking this might be accomplished by an LOD expression, but not sure where to start.
You can achieve this without needing a LOD calculation. Simply change your filters from standard blue dimension filters to be context filters. To do this simply right click on the filter when it is in the filter pane and click "Add to Context". The filter will be shown as grey. Now all ranks will be calculated after filters have been apllied
Why does this work? It is to do with the Order of Operations in Tableau. A calculation such as rank is a table calculation. As the name implies the calculation is processed on the entire data table before dimension filters are applied. However, when something is a context filter it creates temporary tables which are then used to calculate table cals.
Find out more here: https://www.google.com.au/search?q=order+of+operations+tableau&oq=order+of+operations+tableau&aqs=chrome..69i57j0j69i65j0j69i65j0.3475j0j7&sourceid=chrome&ie=UTF-8
I have a challenge in Oracle Apex - I would to sum multiple columns to give 3 extra rows namely points, Score, %score. There are more columns but I'm only choosing a few for now.
Below is an example structure of my data:
Town | Sector | Outside| Inside |Available|Price
Roy-----Formal----0----------0----------1------0
Kobus --Formal----0 ---------0--------- 1------0
Wika ---Formal----0----------0--------- 1------0
Mevo----Formal----1----------1----------1------0
Hoch----Formal----1----------1----------1------1
Points------------2----------2----------5------1
Score------------10---------10---------10------10
%score-----------20---------20---------50------10
Each column has a constant weighting (which serves as a factor and it can change depending on the areas). In this case, the weighting for the areas are in the first row of the sector Formal:
Sector |Outside| Inside |Available|Price
Formal----1----------1 ----------1-----1
Informal--1----------0 ----------2-----1
I tried using the aggregate sum function in apex but it wont work because I need the factor in the other table. This is where my challenge began.
To compute the rows below the report
points = sum per column * weighting factor per column
Score = sum of no of shops visited (in this case its 5) * weighting factor per column
% score = points/Score * 100
The report should display as described above. With the new computed rows below.
I kindly ask anyone to assist me with this challenge as I have tried searching for solutions but haven't come across any.
Thanks a lot for your support in advance!!